15 openstreetmap

Downloading OpenStreetMap data with a single line of code

Uncomment the following line to install leafmap if needed.

In [1]:

# !pip install geopandas osmnx leafmap

# !pip install geopandas osmnx leafmap

In [2]:

import leafmap

import leafmap

Add OSM data of place(s) by name or ID to the map. Note that the leafmap custom layer control does not support GeoJSON, we need to use the ipyleaflet built-in layer control.

In [3]:

m = leafmap.Map(toolbar_control=False, layers_control=True)
m.add_osm_from_geocode("New York City", layer_name='NYC')
m

m = leafmap.Map(toolbar_control=False, layers_control=True) m.add_osm_from_geocode("New York City", layer_name='NYC') m

Out[3]:

Make this Notebook Trusted to load map: File -> Trust Notebook

In [4]:

m = leafmap.Map(toolbar_control=False, layers_control=True)
m.add_osm_from_geocode("Chicago, Illinois", layer_name='Chicago, IL')
m

m = leafmap.Map(toolbar_control=False, layers_control=True) m.add_osm_from_geocode("Chicago, Illinois", layer_name='Chicago, IL') m

Out[4]:

Make this Notebook Trusted to load map: File -> Trust Notebook

Show OSM feature tags.

https://wiki.openstreetmap.org/wiki/Map_features

In [5]:

# leafmap.osm_tags_list()

# leafmap.osm_tags_list()

Add OSM entities within some distance N, S, E, W of address to the map.

In [6]:

m = leafmap.Map(toolbar_control=False, layers_control=True)
m.add_osm_from_address(
    address="New York City", tags={"amenity": "bar"}, dist=1500, layer_name="NYC bars"
)
m

m = leafmap.Map(toolbar_control=False, layers_control=True) m.add_osm_from_address( address="New York City", tags={"amenity": "bar"}, dist=1500, layer_name="NYC bars" ) m

Out[6]:

Make this Notebook Trusted to load map: File -> Trust Notebook

In [7]:

m = leafmap.Map(toolbar_control=False, layers_control=True)
m.add_osm_from_address(
    address="New York City",
    tags={"landuse": ["retail", "commercial"], "building": True},
    dist=1000,
    layer_name="NYC buildings",
)
m

m = leafmap.Map(toolbar_control=False, layers_control=True) m.add_osm_from_address( address="New York City", tags={"landuse": ["retail", "commercial"], "building": True}, dist=1000, layer_name="NYC buildings", ) m

Out[7]:

Make this Notebook Trusted to load map: File -> Trust Notebook

Add OSM entities within a N, S, E, W bounding box to the map.

In [8]:

m = leafmap.Map(toolbar_control=False, layers_control=True)
north, south, east, west = 40.7551, 40.7454, -73.9738, -73.9965
m.add_osm_from_bbox(
    north, south, east, west, tags={"amenity": "bar"}, layer_name="NYC bars"
)
m

m = leafmap.Map(toolbar_control=False, layers_control=True) north, south, east, west = 40.7551, 40.7454, -73.9738, -73.9965 m.add_osm_from_bbox( north, south, east, west, tags={"amenity": "bar"}, layer_name="NYC bars" ) m

Out[8]:

Make this Notebook Trusted to load map: File -> Trust Notebook

Add OSM entities within some distance N, S, E, W of a point to the map.

In [9]:

m = leafmap.Map(
    center=[46.7808, -96.0156], zoom=12, toolbar_control=False, layers_control=True
)
m.add_osm_from_point(
    center_point=(46.7808, -96.0156),
    tags={"natural": "water"},
    dist=10000,
    layer_name="Lakes",
)
m

m = leafmap.Map( center=[46.7808, -96.0156], zoom=12, toolbar_control=False, layers_control=True ) m.add_osm_from_point( center_point=(46.7808, -96.0156), tags={"natural": "water"}, dist=10000, layer_name="Lakes", ) m

Out[9]:

Make this Notebook Trusted to load map: File -> Trust Notebook

In [10]:

m = leafmap.Map(
    center=[39.9170, 116.3908], zoom=15, toolbar_control=False, layers_control=True
)
m.add_osm_from_point(
    center_point=(39.9170, 116.3908),
    tags={"building": True, "natural": "water"},
    dist=1000,
    layer_name="Beijing",
)
m

m = leafmap.Map( center=[39.9170, 116.3908], zoom=15, toolbar_control=False, layers_control=True ) m.add_osm_from_point( center_point=(39.9170, 116.3908), tags={"building": True, "natural": "water"}, dist=1000, layer_name="Beijing", ) m

Out[10]:

Make this Notebook Trusted to load map: File -> Trust Notebook

Add OSM entities within the current map view to the map.

In [11]:

m = leafmap.Map(toolbar_control=False, layers_control=True)
m.set_center(-73.9854, 40.7500, 16)
m

m = leafmap.Map(toolbar_control=False, layers_control=True) m.set_center(-73.9854, 40.7500, 16) m

Out[11]:

Make this Notebook Trusted to load map: File -> Trust Notebook

The add_osm_from_view() is only available for the ipyleaflet plotting backend.

In [12]:

# m.add_osm_from_view(tags={"amenity": "bar", "building": True}, layer_name="New York")

# m.add_osm_from_view(tags={"amenity": "bar", "building": True}, layer_name="New York")

Create a GeoPandas GeoDataFrame from place.

In [13]:

gdf = leafmap.osm_gdf_from_place("New York City", tags={"amenity": "bar"})
gdf

gdf = leafmap.osm_gdf_from_place("New York City", tags={"amenity": "bar"}) gdf

/opt/hostedtoolcache/Python/3.9.15/x64/lib/python3.9/site-packages/osmnx/utils.py:192: UserWarning: The `utils.config` function is deprecated and will be removed in a future release. Instead, use the `settings` module directly to configure a global setting's value. For example, `ox.settings.log_console=True`.
  warnings.warn(

Out[13]:

		addr:city	addr:country	addr:housenumber	addr:postcode	addr:state	addr:street	amenity	ele	gnis:county_name	gnis:feature_id	...	building:levels	disused:amenity	screen	drink:cocktails	building:colour	roof:material	roof:shape	roof:colour	ways	type
element_type	osmid
node	368043598	New York	US	53	10014	NY	Christopher Street	bar	7	New York	2082946	...	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN
	419366609	NaN	NaN	NaN	NaN	NaN	NaN	bar	NaN	NaN	NaN	...	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN
	419367969	NaN	NaN	NaN	NaN	NaN	NaN	bar	NaN	NaN	NaN	...	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN
	484078905	Brooklyn	NaN	388	11211	NY	Union Avenue	bar	NaN	NaN	NaN	...	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN
	617740843	NaN	NaN	NaN	NaN	NaN	NaN	bar	NaN	NaN	NaN	...	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN
...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...
way	637354701	NaN	NaN	308	11238	NaN	Flatbush Avenue	bar	NaN	NaN	NaN	...	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN
	664632831	NaN	NaN	1840	10128	NaN	2nd Avenue	bar	NaN	NaN	NaN	...	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN
	665897391	New York	NaN	54	10001	NaN	West 31st Street	bar	NaN	NaN	NaN	...	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN
	1073233725	NaN	NaN	9259	11209	NaN	4th Avenue	bar	NaN	NaN	NaN	...	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN
relation	12554650	NaN	NaN	NaN	NaN	NaN	NaN	bar	NaN	NaN	NaN	...	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	[278963046, 278963089]	multipolygon

1078 rows × 180 columns

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Last update: 2022-11-20
Created: 2021-05-26